Signal processing apparatus and method for generating a corrected image having a large number of pixels from an image having a lesser number of pixels, and recording medium having a program recorded thereon for performing such method

ABSTRACT

A signal processing apparatus includes a generator operable to generate a second image signal by converting a first image signal into the second image signal; a calculation unit operable to calculate a correction amount based on an evaluation of the second image signal relative to the first image signal; and a correction unit operable to correct the second image signal based on the correction amount.

CROSS-REFERENCE TO RELATED APPLICATIONS

The present application claims priority from Japanese Patent ApplicationNo. JP 2004-124270 filed Apr. 20, 2004, the disclosure of which ishereby incorporated by reference herein.

BACKGROUND OF THE INVENTION

The present invention relates to signal processing apparatuses andmethods and to recording media and programs for controlling the signalprocessing apparatuses and methods, and more particularly, to a signalprocessing apparatus and method capable of generating high-qualityimages and to a recording medium and a program for controlling suchsignal processing apparatus and method.

Recently, due to an increase in the size of display screens fortelevision receivers, images often have been displayed using imagesignals having a large number of pixels. Thus, for example, processingfor converting pixels into quadruple-density pixels in order to convertstandard-definition (SD) images into high-definition (HD) images issuggested, for example, in Japanese Unexamined Patent ApplicationPublication No. 2000-78536. Thus, viewers can view higher-quality imageson large screens.

However, when an output image is generated using a linear predictioncoefficient, a unique output image is determined from an input image. Inaddition, for example, when a method is adopted for performingclassification by adaptive dynamic range coding (ADRC), for reading anoptimal prediction coefficient from among prediction coefficientslearned in advance in accordance with the classification, and forgenerating an output image in accordance with the predictioncoefficient, a unique output image is determined depending on the inputimage. Although in order to reduce the error between an input image andan output image, a prediction coefficient is generated by learning manysupervisor images in advance, the error may not be satisfactorilyreduced for some input images.

In such cases, the high-resolution images that are generated have beenoutput as they are. For example, by quadruple-density conversion, fourpixels are generated from one pixel using respective independent linearprediction coefficients. Since the characteristics of the processingperformed between the four pixels are different from the characteristicsof the processing performed between another four pixels acquired fromanother input pixel, discontinuity may occur.

As a result, users may not be able to view images with high quality.

SUMMARY OF THE INVENTION

It is desirable to provide images with higher quality.

According to an embodiment of the present invention, a signal processingapparatus includes a generator operable to generate a second imagesignal by converting a first image signal into the second image signal;a calculation unit operable to calculate a correction amount based on anevaluation of the second image signal relative to the first imagesignal; and a correction unit operable to correct the second imagesignal based on the correction amount.

A block of pixels from among pixels constituting the second image signalincludes a target pixel, and the calculation unit may calculate acoefficient representing the evaluation based on the relationshipbetween a first difference between the target pixel and pixels otherthan the target pixel within the block of pixels and a second differencebetween the target pixel and pixels outside the block of pixels.

The calculation unit may include a first difference calculation unitoperable to calculate the first difference between the target pixel andthe pixels other than the target pixel within the block of pixels; asecond difference calculation unit operable to calculate the seconddifference between the target pixel and the pixels outside the block ofpixels; a first average value calculation unit operable to calculate theaverage of the first differences in a frame; a second average valuecalculation unit operable to calculate the average of the seconddifferences in the frame; a coefficient calculation unit operable tocalculate the coefficient based on a ratio of the average of the firstdifferences in the frame and the average of the second differences inthe frame; and a correction amount calculation unit operable tocalculate the correction amount based on the coefficient and the seconddifference.

According to an embodiment of the present invention, a signal processingmethod includes generating a second image signal by converting a firstimage signal into the second image signal; calculating a correctionamount based on an evaluation of the second image signal relative to thefirst image signal; and correcting the second image signal based on thecorrection amount.

According to an embodiment of the present invention, a recording mediumis recorded with a computer-readable program for performing a signalprocessing method, the method including generating a second image signalby converting a first image signal into the second image signal;calculating a correction amount based on an evaluation of the secondimage signal relative to the first image signal; and correcting thesecond image signal based on the correction amount.

According to an embodiment of the present invention, a system forperforming a signal processing method includes a processor operable toexecute instructions; and instructions, the instructions includinggenerating a second image signal by converting a first image signal intothe second image signal; calculating a correction amount based on anevaluation of the second image signal relative to the first imagesignal; and correcting the second image signal based on the correctionamount.

Accordingly, a correction amount is calculated in accordance with anevaluation of a second image signal relative to a first image signal,the second image signal being generated by performing pixel conversionon the first image signal, and the second image signal is correctedbased on the correction amount.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram showing an example of the functional structureof a signal processing apparatus according to an embodiment of thepresent invention;

FIG. 2 is a flowchart of an image signal generation process performed bythe signal processing apparatus shown in FIG. 1;

FIG. 3 is a block diagram showing an example of the functional structureof an HD prediction section shown in FIG. 1;

FIG. 4 is a flowchart of an HD prediction value generation process;

FIG. 5 is an illustration for explaining the relationship between SDpixel data and HD pixel data;

FIG. 6 is a block diagram showing an example of the functional structureof a prediction value evaluation section shown in FIG. 1;

FIG. 7 is an illustration for explaining modes;

FIG. 8 is an illustration for explaining an intra-mode difference and aninter-mode difference;

FIG. 9 is an illustration for explaining the intra-mode difference andthe inter-mode difference;

FIG. 10 is an illustration for explaining the intra-mode difference andthe inter-mode difference;

FIG. 11 is an illustration for explaining the intra-mode difference andthe inter-mode difference;

FIG. 12 is a flowchart of a correction amount calculation process;

FIG. 13 is an illustration for explaining the principle of correction;and

FIG. 14 is a block diagram showing an example of the structure of apersonal computer.

DETAILED DESCRIPTION

Embodiments of the present invention will be described with reference tothe drawings.

FIG. 1 shows an example of the functional structure of a signalprocessing apparatus 1 according to an embodiment of the presentinvention. The signal processing apparatus 1 includes an HD predictionsection 11, a prediction value evaluation section 12, and a predictionvalue correction section 13.

An input image signal is input to the HD prediction section 11. Forexample, when the input image signal is an SD image signal, the HDprediction section 11 converts the SD image signal into an HD imagesignal and outputs the HD image signal as a signal Y₁ to the predictionvalue evaluation section 12 and the prediction value correction section13. The prediction value evaluation section 12 evaluates the HD imagesignal received as a prediction value from the HD prediction section 11,calculates a correction amount E, and supplies the correction amount Eto the prediction value correction section 13. The prediction valuecorrection section 13 corrects the HD image signal received from the HDprediction section 11 in accordance with the correction amount Esupplied from the prediction value evaluation section 12, and outputs anoutput image signal as a signal Y₂.

A process for generating an image signal performed by the signalprocessing apparatus 1 shown in FIG. 1 is described next with referenceto the flowchart shown in FIG. 2.

In step S1, the HD prediction section 11 generates an HD predictionvalue from an input image signal. In other words, the HD predictionsection 11 generates an HD image signal, as an HD prediction value, froma received SD image signal, and outputs the generated HD image signal tothe prediction value evaluation section 12 and the prediction valuecorrection section 13. A process for generating the HD prediction valuewill be described below with reference to FIGS. 3 and 4.

In step S2, the prediction value evaluation section 12 evaluates the HDprediction value received from the HD prediction section 11. Theoperation of the prediction value evaluation section 12 will bedescribed below with reference to FIGS. 6 and 12. Accordingly, theprediction value generated by the HD prediction section 11 is evaluated,and a correction amount E is calculated in accordance with theevaluation.

In step S3, the prediction value correction section 13 corrects the HDprediction value. In other words, a signal Y₂, as a corrected HD imagesignal, is calculated by subtracting the correction amount E suppliedfrom the prediction value evaluation section 12 from the predictionvalue Y₁, which is the HD image signal supplied from the HD predictionsection 11, in accordance with equation (1).Y ₂ =Y ₁ −E   (1)

FIG. 3 is a block diagram showing the functional structure of the HDprediction section 11. As shown in FIG. 3, the HD prediction section 11includes a prediction tap extraction unit 31, a class tap extractionunit 32, a classification unit 33, a coefficient storage unit 34, and anadaptive prediction unit 35.

The prediction tap extraction unit 31 extracts a prediction tap from theSD image signal, which is an input image signal, and supplies theextracted prediction tap to the adaptive prediction unit 35. The classtap extraction unit 32 extracts a class tap from the received SD imagesignal, and outputs the extracted class tap to the classification unit33. The position of a pixel in the received SD image signal that isextracted as the prediction tap by the prediction tap extraction unit 31and the position of a pixel in the received SD image signal that isextracted as the class tap by the class tap extraction unit 32 aredetermined in advance.

The classification unit 33 determines a class in accordance with thevalue of a pixel constituting the class tap received from the class tapextraction unit 32, and outputs code corresponding to the class to thecoefficient storage unit 34. Prediction coefficients generated for eachclass by learning many images in advance are stored in the coefficientstorage unit 34. The coefficient storage unit 34 reads the predictioncoefficient corresponding to the class received from the classificationunit 33, and outputs the prediction coefficient to the adaptiveprediction unit 35. The adaptive prediction unit 35 applies the value ofthe pixel constituting the prediction tap extracted by the predictiontap extraction unit 31 and the prediction coefficient supplied from thecoefficient storage unit 34 to a first linear combination formula, andgenerates an HD image signal as an HD prediction value.

A process for generating an HD prediction value performed by the HDprediction section 11 is described next with reference to the flowchartshown in FIG. 4.

In step S31, the class tap extraction unit 32 extracts a class tap froma received SD image signal. The extracted class tap is supplied to theclassification unit 33. In step 32, the classification unit 33 performsclassification. In other words, a class is determined by performing, forexample, 1-bit ADRC processing on the value of the class tap receivedfrom the class tap extraction unit 32. The determined class correspondsto the characteristics of the received SD image signal. In step S33, thecoefficient storage unit 34 reads a prediction coefficient. Morespecifically, the prediction coefficient corresponding to the class codereceived from the classification unit 33 is read, and the readprediction coefficient is supplied to the adaptive prediction unit 35.Since this class code corresponds to the characteristics of the receivedSD image signal, the prediction coefficient corresponds to thecharacteristics of the SD image signal.

In step S34, the prediction tap extraction unit 31 extracts a predictiontap. The extracted prediction tap is supplied to the adaptive predictionunit 35. In step S35, the adaptive prediction unit 35 generates an HDprediction value. In other words, the HD prediction value is calculatedby applying the pixel value of the prediction tap supplied from theprediction tap extraction unit 31 and the prediction coefficient read bythe coefficient storage unit 34 to a predetermined first linearprediction formula.

As described above, for example, as shown in FIG. 5, HD pixel datarepresented by squares having four times the pixel density is generatedfrom SD pixel data represented by circles. In this case, as shown inFIG. 5, for example, one piece of SD pixel data p1 corresponds to fourpieces of HD pixel data q1 to q4 around the SD pixel data p1.

As described above, a higher-density HD image signal generated from anSD image signal is supplied to the prediction value evaluation section12 and the prediction value correction section 13.

FIG. 6 shows an example of the functional structure of the predictionvalue evaluation section 12. The prediction value evaluation section 12includes an intra-mode difference calculator 61, an average valuecalculator 62, a correction coefficient calculator 63, a correctionamount calculator 64, an inter-mode difference calculator 65, and anaverage value calculator 66.

The intra-mode difference calculator 61 calculates an intra-modedifference value of HD prediction values supplied from the adaptiveprediction unit 35 of the HD prediction section 11. Similarly, theinter-mode difference calculator 65 calculates an inter-mode differencevalue of the received HD prediction values. In this embodiment, as shownin FIG. 7, with respect to a target pixel in SD pixel data, foursurrounding HD pixels are set to modes 0 to 3. In the example shown inFIG. 7, an HD pixel on the upper left of the target pixel is set to themode 0, an HD pixel on the upper right of the target pixel is set to themode 1, an HD pixel on the lower left of the target pixel is set to themode 2, and an HD pixel on the lower right of the target pixel is set tothe mode 3.

As shown in FIG. 8, four pixels m0, m1, m2, and m3 in the modes 0, 1, 2,and 3 constitute a mode block. One of the pixels m0 to m3 is set as atarget pixel, and the difference between the target pixel and the otherpixels in the mode block is calculated as an intra-mode difference. Inthe example shown in FIG. 8, the upper-left pixel m0 in the mode 0 isset as the target pixel. Thus, the difference between the target pixelm0 in the mode 0 and the pixel m1 in the mode 1, the pixel m2 in themode 2, and the pixel m3 in the mode 3 is calculated as an intra-modedifference. In other words, the intra-mode difference D_(in) isrepresented by equation (2).D _(in) =|m0−m1|+|m0−m2|+|m0−m3|  (2)

As is clear from equation (2), in this example, the sum of the absolutevalues of the differences between the target pixel and the pixels in theother three modes is obtained as the intra-mode difference D_(in).

In contrast, the difference between the target pixel and pixels that arenot within the mode block for the target pixel is obtained as aninter-mode difference. In other words, in the example shown in FIG. 8,since the target pixel m0 is on the upper left corner of the mode block,the difference between the target pixel m0 and pixels s1, s2, and s3,which are on the left, above, and upper left, respectively, of thetarget pixel m0, is an inter-mode difference. In other words, theinter-mode difference D_(out) is calculated using equation (3) as thesum of the absolute values of the differences between the target pixelm0 and the pixel s1, which is on the left of the target pixel m0,between the target pixel m0 and the pixel s2, which is above the targetpixel m0, and between the target pixel m0 and the pixel s3, which is onthe upper left of the target pixel m0.D _(out) =|m0−s1|+|m0−s2|+|m0−s3|  (3)

For example, if the pixel m0 located on the upper right corner of themode block is set as the target pixel, as shown in FIG. 9, the sum ofthe absolute values of the differences between the target pixel m0 andthe pixel s1, which is on the right of the target pixel m0, between thetarget pixel m0 and the pixel s2, which is above the target pixel m0,and between the target pixel m0 and the pixel s3, which is on the upperright of the target pixel m0, is obtained as the inter-mode differenceD_(out).

In FIG. 9, the sum of the absolute values of the differences between thetarget pixel m0 and the other three pixels m1, m2, and m3 in the modeblock is obtained as the intra-mode difference D_(in), as in the exampleshown in FIG. 8.

For example, if the pixel m0 located on the lower left corner of themode block is set as the target pixel, as shown in FIG. 10, the sum ofthe absolute values of the differences between the target pixel m0 andthe pixel s1, which is on the left of the target pixel m0, between thetarget pixel m0 and the pixel s2, which is below the target pixel m0,and between the target pixel m0 and the pixel s3, which is on the lowerleft of the target pixel m0, is obtained as the inter-mode differenceD_(out). The sum of the absolute values of the differences between thetarget pixel m0 and the other three pixels m1, m2, and m3 in the modeblock is obtained as the intra-mode difference D_(in).

For example, if the pixel m0 located on the lower right corner of themode block is set as the target pixel, the sum of the absolute values ofthe differences between the target pixel m0 and the pixel s1, which ison the right of the target pixel m0, between the target pixel m0 and thepixel s2, which is below the target pixel m0, and between the targetpixel m0 and the pixel s3, which is on the lower right of the targetpixel m0, is obtained as the inter-mode difference D_(out), The sum ofthe absolute values of the differences between the target pixel m0 andthe other three pixels m1, m2, and m3 in the mode block is obtained asthe intra-mode difference D_(in).

Referring back to FIG. 6, the average value calculator 62 calculates anintra-mode difference average D_(inav), which is the average of theintra-mode differences in a frame calculated by the intra-modedifference calculator 61. The average value calculator 66 calculates aninter-mode difference average D_(outav), which is the average of theinter-mode differences in the frame calculated by the inter-modedifference calculator 65.

The correction coefficient calculator 63 calculates a correctioncoefficient K using equation (4) in accordance with the intra-modedifference average D_(inav) calculated by the average value calculator62 and the inter-mode difference average D_(outav) calculated by theaverage value calculator 66.

$\begin{matrix}{K = \frac{D_{inav}}{D_{outav}}} & (4)\end{matrix}$

The correction amount calculator 64 calculates a correction amount Eusing equation (5) in accordance with the correction coefficient Kcalculated by the correction coefficient calculator 63 and an inter-modedifference d_(out) calculated by the inter-mode difference calculator65.

$\begin{matrix}{E = {( {1 - K} ) \times \frac{d_{out}}{2}}} & (5)\end{matrix}$

The inter-mode difference d_(out) used in equation (5) is obtained byequation (6).

$\begin{matrix}{d_{out} = \frac{\{ {( {{m\; 0} - {s\; 1}} ) + ( {{m\; 0} - {s\; 2}} ) + ( {{m\; 0} - {s\; 3}} )} \}}{3}} & (6)\end{matrix}$

A process for calculating a correction amount performed by theprediction value evaluation section 12 is described next with referenceto the flowchart shown in FIG. 12.

In step S61, the intra-mode difference calculator 61 calculates anintra-mode difference. More specifically, a mode block is arranged in apredetermined position of a frame constituted by HD pixel data, and apixel from among four pixels constituting the mode block is set as atarget pixel. The intra-mode difference D_(in) is calculated inaccordance with equation (2). In step S62, the inter-mode differencecalculator 65 calculates an inter-mode difference D_(out) in accordancewith equation (3).

Calculation of intra-mode differences and calculation of inter-modedifferences are performed by the intra-mode difference calculator 61 andthe inter-mode difference calculator 65, respectively, for all thepixels in the frame by sequentially moving the position of the modeblock within the frame.

In step S63, the average value calculator 62 calculates the intra-modedifference average D_(inav), which is the average of the intra-modedifferences D_(in) in the frame calculated by the intra-mode differencecalculator 61. Similarly, in step S64, the average value calculator 66calculates the inter-mode difference average D_(outav), which is theaverage of the inter-mode differences D_(out) in the frame calculated bythe inter-mode difference calculator 65.

In step S65, the correction coefficient calculator 63 calculates acorrection coefficient K. In other words, the correction coefficientcalculator 63 calculates the correction coefficient K in accordance withequation (4) by dividing the intra-mode difference average D_(inav)calculated by the average value calculator 62 by the inter-modedifference average D_(outav) calculated by the average value calculator66.

In step S66, the correction amount calculator 64 calculates a correctionamount E represented by equation (5) in accordance with the correctioncoefficient K calculated by the correction coefficient calculator 63 andthe inter-mode difference d_(out) represented by equation (6),calculated by the inter-mode difference calculator 65.

The correction coefficient K and the correction amount E are explainedas described below.

In a general natural image, an intra-mode difference average D_(inav)and an inter-mode difference average D_(outav) are equal to each other,as represented by equation (7).D_(inav)=D_(outav)   (7)

Equation (7) means that there is no direction dependency in the pixellevel gradient.

In this embodiment, however, since quadruple-density conversion isperformed on a pixel, gaps are generated between blocks each constitutedby four pixels in the converted image. Thus, the inter-mode differenceaverage D_(outav) is greater than the intra-mode difference averageD_(inav), as represented by condition (8).D_(inav)<D_(outav)   (8)

In other words, on average, the inter-mode difference is greater thanthe intra-mode difference. This is because four HD pixels are generatedfrom one SD pixel and this output is independently performed for eachfour pixels.

As described above, the values that should be equal to each other onaverage, as represented by equation (7), are not equal to each other inan image after pixel conversion, as represented by condition (8). Thus,correcting the values so as to be equal to each other enables thecalculation result to be approximated to a desired image to be output(an image with higher accuracy).

Since, as represented by equation (7), the intra-mode difference averageD_(inav) and the inter-mode difference average D_(outav) are equal toeach other in the original image on which pixel conversion is notperformed, the correction coefficient K represented by equation (4)represents how much smaller than the inter-mode difference, serving asthe output result of the quadruple-density processing, the inter-modedifference in the original image is. Thus, approximating the inter-modedifference D_(out) of the image, serving as the output result ofquadruple-density processing, to the intra-mode difference D_(in)corrects the image in the correct direction.

FIG. 13 shows this processing conceptually. As shown at the leftmostpart in FIG. 13, the difference d0 between the target pixel m0 and thepixel s1 that is on the left of the target pixel m0 and that is outsidethe mode block for the target pixel m0 is obtained.

When quadruple-density pixel conversion is performed on this image, asshown at the center in FIG. 13, the difference between the target pixelm0 and the pixel s1 increases from d0 to d1 on average. This is thestate of the signal Y₁ that is output as the HD prediction value fromthe HD prediction section 11.

Multiplying the correction coefficient K, which represents how muchsmaller than the difference d1 the difference d0 in the original imageis, by the difference d1 enables the corrected difference d2 to beapproximated to the original difference d0. The amount of correctionused here is the correction amount E.

Since the processing for correcting the difference between the targetpixel m0 and the pixel s1 is performed from two sides (correctionperformed when the pixel m0 functions as a target pixel and correctionperformed when the pixel s1 functions as a target pixel), the correctionamount E is divided by two in equation (5).

The prediction value correction section 13 calculates the signal Y₂,which is the corrected HD image signal, by subtracting the correctionamount E from the signal Y₁ output from the HD prediction section 11 inaccordance with equation (1). Thus, on average, the inter-modedifference average approximates the intra-mode difference average in thewhole screen, and an image without gaps between mode blocks can beachieved.

Although a case where quadruple-density pixel conversion is performedhas been described, the multiplication factor is not limited to four. Inaddition, n-times density pixel conversion is not necessarily performed.1/n-times density pixel conversion can also be performed.

The present invention is also applicable to television receivers, harddisk recorders, and other apparatuses for processing image signals.

The foregoing series of processes may be performed by hardware orsoftware. In this case, for example, the signal processing apparatus 1may include a personal computer shown in FIG. 14.

Referring to FIG. 14, a central processing unit (CPU) 221 performsvarious types of processing in accordance with a program stored in aread-only memory (ROM) 222 or a program loaded into a random-accessmemory (RAM) 223 from a storage unit 228. Data necessary for the CPU 221to perform the various types of processing is appropriately stored inthe RAM 223.

The CPU 221, the ROM 222, and the RAM 223 are connected to each othervia a bus 224. An input/output interface 225 is connected to the bus224.

The input/output interface 225 is connected to an input unit 226including a keyboard, a mouse, and the like; an output unit 227including a display, such as a cathode-ray tube (CRT) or a liquidcrystal device (LCD), and a speaker; the storage unit 228, such as ahard disk; and a communication unit 229, such as a modem. Thecommunication unit 229 performs communication via a network includingthe Internet.

A drive 230 is connected to the input/output interface 225 according toneed. A removable medium 231, such as a magnetic disk, an optical disk,a magneto-optical disk, or a semiconductor memory, is appropriatelyinstalled on the drive 230. A computer program read from the removablemedium 231 is installed in the storage unit 228 according to need.

When the series of the foregoing processes is performed by software, aprogram constituting the software is installed via a network or arecording medium on a computer built in dedicated hardware or ageneral-purpose personal computer or the like capable of performingvarious functions by installing various programs.

As shown in FIG. 14, the recording medium not only includes theremovable medium 231, such as a magnetic disk (including a flexibledisk), an optical disk (including a compact disk-read only memory(CD-ROM) and a digital versatile disk (DVD)), a magneto-optical disk(including a MiniDisk (MD)), or a semiconductor memory, which isrecorded with the program and is distributed in order to provide theprogram to a user independently of the apparatus main unit, but alsoincludes the ROM 222 or the storage unit 228, such as a hard disk, whichis built in the apparatus main unit to be provided to the user and whichis recorded with the program.

In this specification, steps for a program recorded in the recordingmedium are not necessarily performed in chronological order inaccordance with the written order. The steps may be performed inparallel or independently without being performed in chronologicalorder.

In addition, in this specification, a system means the whole equipmentincluding a plurality of apparatuses.

The present invention is also applicable to a personal computerperforming image processing.

According to the foregoing embodiments, high-resolution images withhigher quality can be generated.

Although the invention herein has been described with reference toparticular embodiments, it is to be understood that these embodimentsare merely illustrative of the principles and applications of thepresent invention. It is therefore to be understood that numerousmodifications may be made to the illustrative embodiments and that otherarrangements may be devised without departing from the spirit and scopeof the present invention as defined by the appended claims.

1. A signal processing apparatus comprising: a generator operable togenerate a second image signal by converting a first image signal intothe second image signal; a calculation unit operable to calculate acorrection amount based on an evaluation of the second image signalrelative to the first image signal, said evaluation involvingcalculating a first difference by using pixels within a block of pixelswhich includes a target pixel and calculating a second difference byusing pixels outside the block of pixels; and a correction unit operableto correct the second image signal based on the correction amount.
 2. Asignal processing apparatus, comprising: a generator operable togenerate a second image signal by converting a first image signal intothe second image signal; a calculation unit operable to calculate acorrection amount based on an evaluation of the second image signalrelative to the first image signal; and a correction unit operable tocorrect the second image signal based on the correction amount, whereina block of pixels from among pixels constituting the second image signalincludes a target pixel, and the calculation unit calculates acoefficient representing the evaluation based on a relationship betweena first difference between the target pixel and pixels other than thetarget pixel within the block of pixels and a second difference betweenthe target pixel and pixels outside the block of pixels.
 3. The signalprocessing apparatus according to claim 2, wherein the calculation unitincludes: a first difference calculation unit operable to calculate thefirst difference between the target pixel and the pixels other than thetarget pixel within the block of pixels; a second difference calculationunit operable to calculate the second difference between the targetpixel and the pixels outside the block of pixels; a first average valuecalculation unit operable to calculate an average of the firstdifferences in a frame; a second average value calculation unit operableto calculate an average of the second differences in the frame; acoefficient calculation unit operable to calculate the coefficient basedon a ratio of the average of the first differences in the frame and theaverage of the second differences in the frame; and a correction amountcalculation unit operable to calculate the correction amount based onthe coefficient and the second difference.
 4. A signal processingmethod, comprising: generating a second image signal by converting afirst image signal into the second image signal; calculating acorrection amount based on an evaluation of the second image signalrelative to the first image signal, said evaluation involvingcalculating a first difference by using pixels within a block of pixelswhich includes a target pixel and calculating a second difference byusing pixels outside the block of pixels; and correcting the secondimage signal based on the correction amount.
 5. A recording mediumrecorded with a computer-readable program for performing a signalprocessing method, the method comprising: generating a second imagesignal by converting a first image signal into the second image signal;calculating a correction amount based on an evaluation of the secondimage signal relative to the first image signal, said evaluationinvolving calculating a first difference by using pixels within a blockof pixels which includes a target pixel and calculating a seconddifference by using pixels outside the block of pixels; and correctingthe second image signal based on the correction amount.
 6. A system forperforming a signal processing method, the system comprising: aprocessor operable to execute instructions; and instructions, theinstructions including: generating a second image signal by converting afirst image signal into the second image signal; calculating acorrection amount based on an evaluation of the second image signalrelative to the first image signal, said evaluation involvingcalculating a first difference by using pixels within a block of pixelswhich includes a target pixel and calculating a second difference byusing pixels outside the block of pixels; and correcting the secondimage signal based on the correction amount.
 7. A signal processingapparatus, comprising: generating means for generating a second imagesignal by converting a first image signal into the second image signal;calculation means for calculating a correction amount based on anevaluation of the second image signal relative to the first imagesignal, said evaluation involving calculating a first difference byusing pixels within a block of pixels which includes a target pixel andcalculating a second difference by using pixels outside the block ofpixels; and correction means for correcting the second image signalbased on the correction amount.
 8. The signal processing apparatusaccording to claim 1, wherein the calculation unit calculates acoefficient representing the evaluation in accordance with arelationship between the first difference and the second difference, andin which calculating of the first difference involves obtaining adifference between the target pixel and the pixels other than the targetpixel within the block of pixels which is among pixels constituting thesecond image and calculating of the second difference involves obtaininga difference between the target pixel and the pixels outside the blockof pixels.